Function build_chat_agent

openkb/agent/query.py:106–229

Build the chat agent: query agent + a write tool restricted to `` /wiki/explorations/**`` and `` /output/**`` + a ``ShellTool`` advertising locally-installed Anthropic-style skills. This is the variant used by the interactive ``openkb chat`` REPL so users can iterate on genera

(
    kb_dir: Path,
    model: str,
    language: str = "en",
)

def build_chat_agent(
    kb_dir: Path,
    model: str,
    language: str = "en",
) -> Agent:
    """Build the chat agent: query agent + a write tool restricted to
    ``<kb>/wiki/explorations/**`` and ``<kb>/output/**`` + a ``ShellTool``
    advertising locally-installed Anthropic-style skills.

    This is the variant used by the interactive ``openkb chat`` REPL so users
    can iterate on generated artifacts (e.g. ``output/skills/<name>/``) via
    natural-language follow-ups without giving the agent unrestricted write
    access to the wiki.

    Skill discovery: ``openkb/agent/skills.scan_local_skills`` looks in
    ``<kb>/skills/``, ``~/.openkb/skills/``, ``~/.claude/skills/`` for
    ``SKILL.md`` files. Any found skill is exposed to the agent via
    ``ShellTool.environment.skills`` so the model can ``cat`` the skill body
    and follow its instructions when the user&#x27;s request matches.
    """
    wiki_root = str(kb_dir / "wiki")
    kb_root = str(kb_dir)
    base = build_query_agent(wiki_root, model, language=language)

    @function_tool
    def write_file(path: str, content: str) -> str:
        """Write a text file under the KB.

        Allowed paths (relative to KB root):
          * ``wiki/explorations/**`` — chat-derived notes.
          * ``output/**``            — generator artifacts (skills, etc.).

        Any other path is rejected. Parent directories are created.

        Args:
            path: File path relative to KB root
                (e.g. ``"output/skills/demo/SKILL.md"``).
            content: Full text content to write (overwrites if file exists).
        """
        return write_kb_file(path, content, kb_root)

    extra_tools: list = [write_file]
    skill_instructions_addendum = ""

    # Skill discovery via function tools. The agents SDK has a richer
    # ``ShellTool``+``ShellToolLocalSkill`` mechanism for this, but those
    # are OpenAI Responses-API hosted tools; LiteLLM routes through
    # ChatCompletions which rejects hosted tools. So we use plain
    # ``function_tool`` primitives that work with any LiteLLM-routed model.
    from openkb.agent.skills import scan_local_skills

    skills = scan_local_skills(kb_dir)
    skill_index = {s["name"]: s for s in skills}

    if skill_index:
        skill_list_text = _format_skill_list(skills)

        @function_tool